class_docstr: Inherits time series methods from TSM class.
  
  **** DYNAMIC REGRESSION MODEL ****
  
  Parameters
  ----------
  
  formula : string
      patsy string describing the regression
  
  data : pd.DataFrame
      Field to specify the data that will be used
docstr: Creates model latent variables
  
  Returns
  ----------
  None (changes model attributes)
docstr_tok: ["Creates","model","latent","variables","Returns","--","--","--","--","--","None","(","changes","model","attributes",")"]
code: def _create_latent_variables(self):
      """Creates model latent variables
  
      Returns
      ----------
      None (changes model attributes)
      """
  
      self.latent_variables.add_z(
          "Sigma^2 irregular",
          fam.Flat(transform="exp"),
          fam.Normal(0, 3),
      )
  
      for parm in range(self.z_no - 1):
          self.latent_variables.add_z(
              "Sigma^2 " + self.X_names[parm],
              fam.Flat(transform="exp"),
              fam.Normal(0, 3),
          )
  
imports: import copy
  import sys
  import numpy
  import pandas
  import scipy.stats
  from patsy import dmatrices, dmatrix, demo_data
  from ..None import families
  from ..None import tsm
  from ..None import data_check
  from .kalman import *
label_desc: Use image node_id 2 for calling the DynReg obj's underlying member method code with example usage: obj._create_latent_variables() without return types